Financial Integration, Financial Development

and Economic Growth

Jose De Gregorio ∗

Center for Applied EconomicsDepartment of Industrial Engineering

Universidad de Chile

This version: July 1998

Comments Welcome

Abstract

This paper analyzes the relationship between international financial integra-tion and economic growth. Recent literature, surveyed in this paper, empha-sizes the role of financial deepening on economic growth. Less attention hasbeen paid, however, to the role of international financial integration in pro-moting a deep domestic financial market and through that channel fosteringeconomic growth. Financial integration also permits portfolio diversification,allowing higher profitability of investment and, hence, higher rate of economicgrowth. Those issues are examined in this paper. In particular, after review-ing the theory and evidence, this paper analyzes empirically the relationshipsbetween financial integration and financial development, and between financialdevelopment and economic growth.

∗I am grateful to Amar Bhattacharya and Holger Wolf for helpful suggestions, to RossLevine for sharing generously his data, and to Soledad De Gregorio for valuable help. Anyremaining error is my own. e-mail: jdegrego@dii.uchile.cl

1 Introduction

In recent years there has been a large literature highlighting, at both theoret-

ical and empirical level, the importance of having a deep financial system to

promote economic growth. This literature emphasizes the allocative effects of

financial markets, by which they are able to allocate investible funds into their

most profitable uses. At the same time, by pooling risk, financial markets

are able to smooth consumption of individuals having volatile income. Thus,

portfolio diversification allows stable consumption, while investible funds can

be allocated to high-risk high-return activities.

More recently, recent research has looked at these issues from an open e-

conomy point of view. Financial integration with the world economy may

bring similar benefits to those associated with financial deepening. Indeed,

one could think that international financial markets may channel funds to

profitable investment activities, and portfolio diversification in the world may

smooth consumption of households allowing the economy to improve prof-

itability of investment.

These issues are not merely academic questions. On the one hand it is

necessary to know whether developing a deep financial market may be fostered

by international financial integration. On the other hand, and in more practical

terms, financial reforms in developing countries are usually accompanied by an

opening of the capital account, by which domestic financial markets become

not only more competitive, but also more integrated with the rest of the world.

This paper examines the relationship between financial integration and fi-

nancial development and the relationship between financial integration and

economic growth.

For this purpose, the next section discusses the theoretical and empirical

literature on financial development and economic growth. The theoretical

prediction, discussed in section 2, of a positive relationship between financial

development and growth is confirmed by the empirical evidence. Then, in

section 3 the issue about portfolio diversification and consumption smoothing,

and their consequences on economic growth, are discussed.

1

Sections 4 and 5 present the empirical evidence. In section 4, after de-

scribing the data, the relationship between financial integration and financial

development is examined. The results support the view that increased finan-

cial integration increases the depth of the banking system as well as the stock

market. Then, in section 5 the relationship between financial integration and

economic growth is evaluated empirically. Finally, section 6 concludes with

some few final remarks.

2 Overview on Financial Development and Growth

This section surveys some recent literature that examines the effects of finan-

cial development on economic growth, both at the theoretical and the empirical

level.1

2.1 Theory

Economic growth may come from the following two channels: growth in the

amount of factors of production or increases in the efficiency with which those

factors are used. In other words, growth is induced by the increase in invest-

ment (accumulation of capital) and the efficiency of investment.

In a closed economy investment is equal to savings, and this is why savings

is viewed as an important vehicle to increase growth.2 The efficiency of in-

vestment, in turn, includes not only total factor productivity growth, but also

the accumulation of other factors not included in physical capital, and hence,

not included in standard measures of investment. This becomes important as

new theories of economic growth emphasize that we should look at a broader

1For other overviews of the empirical and theoretical literature see De Gregorio and Guidotti (1995), Fry

(1993), Greenwood and Smith (1993), Pagano (1993), and King and Levine (1993), and specially Levine

(1997).

2To simplify the discussion I consider the economy to be closed, so investment equal savings. It could be

assumed that the economy is open and there is in addition an upward sloping-supply of funds (Fry, 1993)

or some other form of imperfect capital mobility such as the lack of collateral to obtain foreign financing for

human capital accumulation (Barro, Mankiw and Sala-i-Martin, 1995). In all of these cases higher national

savings would encourage capital accumulation, and the implications for growth would be qualitatively similar

to those of the closed economy.

2

concept of capital, rather than simply equipment and buildings. We should

also include human capital, organizational capital, information, etc.

Financial development has a dual effect on economic growth. On the one

hand, the development of domestic financial markets may enhance the effi-

ciency of capital accumulation. On the other hand, financial intermediation

may contribute to raising the savings rate and, thus, the investment rate.

The former effect was first emphasized by Goldsmith (1969), who also finds

some positive correlation between financial development and the level of real

per capita GNP. In addition, Goldsmith (1969) also argues that the process

of growth has feedback effects on financial markets by creating incentives for

further financial development.

McKinnon (1973) and Shaw (1973) extend the earlier argument by noting

that financial deepening implies not only higher productivity of capital but also

a higher savings rate and, therefore, a higher volume of investment. Unlike

Goldsmith (1969), where growth and financial intermediation are both thought

of as endogenous, the focus of McKinnon (1973) and Shaw (1973) is on the

effects of public policy regarding financial markets on savings and investment.

In particular, McKinnon (1973) and Shaw (1973) argue that policies that lead

to financial repression—for example, controls which result in negative real

interest rates—reduce the incentives to save. Lower savings, in turn, result in

lower investment and growth. Thus they conclude that higher interest rates

resulting from financial liberalization induce households to increase savings.

The empirical validity of the McKinnon-Shaw hypothesis has been challenged

by various authors. Dıaz-Alejandro (1985), for instance, argues that the Latin

American experience shows that financial deepening is unlikely to increase

savings; therefore, the main contribution of financial deepening to growth

should be thought of as increasing the marginal productivity of capital, rather

than the volume of savings and investment.

Recent theoretical work has incorporated the role of financial factors in

models of endogenous growth in an attempt to analyze formally the interac-

tions between financial markets and long-run economic growth. Greenwood

and Jovanovic (1990) present a model in which both financial intermediation

3

and growth are endogenous.3 In their framework, the role of financial insti-

tutions is to collect and analyze information to channel investible funds to

the investment activities that yield the highest return. Since the activity per-

formed by financial intermediaries involves costs, Greenwood and Jovanovic

(1990) show that there is a positive two-way causal relationship between e-

conomic growth and financial development. On the one hand, the process of

growth stimulates higher participation in financial markets thereby facilitat-

ing the creation and expansion of financial institutions. In the model, agents

need to pay a fixed cost to create a financial intermediary, and hence, the

cost as a fraction of income declines as growth proceeds. On the other hand

financial institutions, by collecting and analyzing information from many po-

tential investors, allow investment projects to be undertaken more efficiently

and, hence, stimulate investment and growth.

Bencivenga and Smith (1991) present a model in which individuals face

uncertainty about their future liquidity needs. They can choose to invest in a

liquid asset—which is safe but has low productivity—and/or an illiquid asset—

which is riskier but has high productivity. In this framework, the presence of

financial intermediation increases economic growth by channelling savings into

the activity with high productivity, while allowing individuals to reduce the

risk associated with their liquidity needs. Although individuals face uncertain

liquidity needs, banks, by the law of large numbers, face a predictable demand

for liquidity and can, therefore, allocate investment funds more efficiently. In

the absence of financial intermediaries, individuals may be forced to liquidate

their investment (i.e., their savings held in illiquid assets) when liquidity needs

arise. Thus, the presence of banks also provides the benefit of eliminating

unnecessary liquidations. Interestingly, Bencivenga and Smith (1991) show in

their model that growth increases even when aggregate savings are reduced as

a result of financial development, the reason being the dominant effect that

financial development has on the efficiency of investment.

Along similar lines, Levine (1992) analyzes the effects of alternative finan-

cial structures on economic growth. In his model, financial institutions raise

3See also Greenwood and Smith (1993).

4

the fraction of total savings devoted to investment and avoid premature liqui-

dations of capital. Banks, stock markets, mutual funds, and investment banks

enhance growth by promoting the efficient allocation of investment through

various channels.

In a somewhat different approach, Roubini and Sala-i-Martin (1992) analyze

the relationship between financial intermediation and growth by emphasizing

the role of government policy. In particular, they develop a model in which

financial repression becomes a tool that governments may use to broaden the

base of the inflation tax. Thus financial repression yields higher seigniorage

to finance government expenditures. In an optimal taxation framework where

the tax instruments at the government’s disposal are the inflation tax and an

income tax that is subject to tax evasion, Roubini and Sala-i-Martin (1992)

show that high income tax evasion induces policymakers to repress the financial

system and set a high inflation rate in an attempt to generate higher revenues

from the inflation tax. Since financial repression reduces the productivity of

capital and lowers savings, it hampers growth.

From a different perspective Jappelli and Pagano (1994) analyze the effects

of financial market developments on the savings rate. They concentrate atten-

tion on the effect of borrowing constraints—that is, the inability of individuals

to borrow freely against future income—on economic growth. This work shifts

the focus from the effects of financial markets on the production side of the e-

conomy to their effects on household behavior. A conclusion from this study is

that the full or partial inability of individuals to borrow against future income

induces them to increase savings. The reason is that when individuals are

unable to borrow, they must build up financial wealth by increasing savings in

order to finance current consumption. Thus, this study suggests that financial

deepening on the side of consumer credit is unlikely to increase savings. This

result is consistent with casual observation in Latin America, where episodes

of financial liberalization have not increased savings rates.

The implication from Jappelli and Pagano (1994) that the relaxation of

borrowing constraints is unlikely to stimulate savings does not necessarily im-

ply that such a form of financial deepening will result in lower growth. De

5

Gregorio (1996), in fact, suggests that the relationship between borrowing

constraints and growth will ultimately depend on the importance of the effect

of borrowing constraints on the marginal productivity of capital relative to

their effect on the volume of savings. In particular, De Gregorio (1996) shows

that a relaxation of borrowing constraints increases the incentives for human

capital accumulation. This effect is likely to increase the marginal product of

capital and, hence, may lead to higher growth despite the reduction in savings.

2.2 Empirical evidence

Recent empirical studies on financial development and growth are based on

regression analysis for large cross-sections of countries, following the important

work of Barro (1991).

The basic equation is:4

γi = α0 + α1FDi + α2Xi + νi (1)

where γi is the rate of growth of country i, FD is an indicator of financial

development, X a set of other determinants of growth, and ν an error term.

The set of variables X usually contains the initial level of GDP to control for

conditional convergence, indices of the level of education, government expen-

diture, macroeconomic indicators, indices of political stability and protection

of property rights, etc.

Several indicators of financial development have been proposed in the lit-

erature. Of course, different indicators will proxy different aspects of the re-

lationship between the financial system and economic performance. Initially,

the indicators were based on monetary aggregates, such as M1 or M2. How-

ever, as argued in De Gregorio and Guidotti (1995), they may provide a poor

proxy of financial development, since they are more related to the ability of

financial systems to provide transaction services, and not necessarily the a-

bility of financial intermediaries to channel funds from savers to borrowers.

Indeed, it is possible that economies with poorly developed financial systems

4See Barro and Sala-i-Martin (1995) for further discussion on the empirical evidence on growth determi-

nants and convergence.

6

be highly monetized, because money may be used as a store of value in the

absence of other, more attractive, alternatives. For this reason, authors such

as Gelb (1989) and King and Levine (1993) use M3, which is also called liquid

liabilities. Estimating (1) using liquid liabilities (LLY ) as indicator of finan-

cial development, for the period 1960–89, gives the following result (King and

Levine, 1993):

γi = 0.024 LLYi + others (2)

(2.67)

R2 = 0.50, N obs. = 77, and t-statistics in parenthesis.

The coefficient of 0.024 “suggests that a country that increased liquid liabilities

from the mean of the slowest growing (0.2) to the mean of the fastest growing

quartile of countries (0.6) . . . would increase its growth rate by almost 1 percent

per annum. Since the difference between the very fast and the very slow

growers is about 5 percent, the rise in LLY alone would eliminate 20 percent

of this difference” (King and Levine, 1993, p. 728).

Although using liquid liabilities overcome some shortcomings of using nar-

rower definitions of money, they may still be influenced by factors other than

financial depth, since M3 still includes M1. For this reason Neal (1988) have

relied on indicators of quasi-liquid liabilities by subtracting M1 from M2, and

along similar lines King and Levine (1992) have subtracted M1 from M3. The

former authors have concluded that the results do not change significantly

when using M3 or M3-M1, because M1 is a small fraction of liquid liabilities.

De Gregorio and Guidotti (1995), and King and Levine (1993) use, alterna-

tively, the ratio of domestic credit to the private sector to GDP as a proxy for

the degree of financial intermediation. It corresponds to credit granted to the

private sector by the central bank and commercial banks (line 32d from the

International Monetary Fund’s International Financial Statistics), as a frac-

tion of GDP, and it will be denoted as CREDIT in what follows.5 The main

advantage of this indicator over other monetary aggregates is that because it

5The results are also very similar when credit form the central bank is excluded.

7

excludes credit to the public sector, it represents more accurately the role of

financial intermediaries in channelling funds to the private sector. Thus, this

is the definition of financial intermediation that should be more closely relat-

ed to the degree of financial intermediation, which should ultimately affect

investment as well as the efficiency of investment.

This measure is, however, only a partial indicator of financial development.

It is a good indicator of financial development that occurs through the bank-

ing system, but may be a weak indicator of financial development that occurs

outside the banking system, e.g., stock markets. This weakness may be more

relevant in industrialized countries, which have experienced significant non-

bank financial innovation. In developing countries, in contrast, most financial

development has occurred within the banking system. Nevertheless, the use of

CREDIT as indicator of financial development fits our purposes of analyzing

the role of banks on development.

Using Barro (1991) dataset for the period 1960-85, De Gregorio and Guidot-

ti (1995) find the following result when using CREDIT to proxy for the degree

of financial development:6

γi = 0.024 CREDITi + others (3)

(3.58)

R2 = 0.54, N obs. = 95,

which again reveals the importance of financial deepening on economic growth.

Next, it is important to disentangle how much of the effect of financial de-

velopment on growth is through increasing investment, and how much through

increasing the efficiency of investment. To examine this issue, equation (3) can

be estimated including the investment rate (INV ) in the set of other variables.

After controlling for investment, the coefficient on CREDIT would capture the

effect of financial development on the efficiency of investment. In contrast, the

6De Gregorio and Guidotti (1995) also report a negative correlation between CREDIT and growth in the

1970s and early 1980s in Latin America. This is explained mainly by the lack of supervision of the banking

system in a period of accelerated liberalization and by serious macroeconomic imbalances. This issues will

not be discussed further in this paper.

8

coefficient in (3) represents the total effect of CREDIT on growth. The equa-

tion that includes investment is:

γi = 0.018 CREDITi + 0.066 INVi + others

(2.30) (1.90)(4)

R2 = 0.57, N obs. = 95.

The coefficient on CREDIT declines from 0.024 to 0.018 when investment

rates are included. This suggests that approximately three-fourths of the effect

of CREDIT on growth is transmitted by increasing the efficiency of investment,

while only one-fourth is transmitted through an increase in investment. Thus,

this finding supports the hypothesis, confirmed by most of the theoretical

literature, that financial intermediation affects growth mainly by increasing

the marginal productivity of capital.

Finally, it has to be noticed that banking development is relatively more

important at early stages of development (De Gregorio and Guidotti (1995)).

As we already saw increasing CREDIT is positively associated with growth,

with a coefficient of 0.024 in regression (3). The sample can be decomposed in

three roughly equally-sized groups of countries, ordered according to the level

of income, to examine whether the importance of banking changes with the

degree of development. In the sample of high-income countries the coefficient

on CREDIT declines to 0.015, while the in the sample of middle-income coun-

tries the coefficient is 0.054, and finally, in the sample of low-income countries

the coefficient reaches its maximum equal to 0.146. Thus, the coefficient on

CREDIT increases tenfold when going from high- to low-income countries.

This finding should not be surprising as many have noted that in industri-

alized countries financial innovation has occurred mostly outside the banking

system. This is confirmed when the analysis is restricted to the period 1970–

85, where actually occurred the boom of non-banking innovation. In this case

the coefficient on CREDIT for high-income countries becomes insignificantly

different from zero. For middle- and low-income countries the coefficients also

decline when the sample is restricted to 1970–85, but they are still positive

and largest in the case of low-income countries.

9

3 Financial Opening and Portfolio Diversification

As discussed in the previous section, financial intermediaries provide individ-

uals with a more diversified portfolio. Thus, an Argentinean investor could

be able to invest in a Malaysian firm, which presumably have profits uncor-

related with Argentina’s stock market. Consequently, individuals would be

able to achieve a more stable (smooth) consumption path. At the same time,

individuals, by protecting themselves against risk, can invest in activities with

more risk, but with a higher yield. Thus the final portfolio could be more

profitable.

For the ensuing discussion I will first focus on the benefits of reducing the

volatility of consumption via financial integration. Then, I turn to the issue

of the potential growth effects stemming from risk-sharing.

The canonical case to assess the effects of reduced volatility of consumption

has been illustrated by Lucas (1987). He considers an economy populated by

a representative consumer that maximizes the following utility function:

U0 ≡ max E

[ ∞∑t=0

(c1−σt − 1)/(1− σ)

](5)

where β ∈ (0, 1) is the discount factor and σ the constant coefficient of risk

aversion. This coefficient is also the inverse of the intertemporal elasticity of

consumption. Consider an individual that has a consumption path growing at

a deterministic rate equal to γ and is subject to stochastic shocks. That is,

ct = c0(1 + γ)tεt (6)

where εt denotes the random variable, that is distributed with mean 1 and

variance s2. The value of U0, the maximized utility, will depend on c0, γ and

s2. Because the utility function is concave, utility increase with c0, and γ, but

decreases with s2. The question is, then, how much the individual is willing to

pay in terms of c0 in order to reach the same level of utility U0, but reducing

the variance of consumption to zero, and thus having a perfectly smooth path

of consumption. To find the solution it is necessary to replace (6) into (5),

compare the values of U0, and then set c0 such that in both cases utility is the

10

same. It can be shown that, after an appropriate approximation, the individual

would be willing to pay at most s2σ/2 percent of current consumption in order

to smooth consumption.

The main conclusion from Lucas (1987) is that the gains from consumption

smoothing are very small, and indeed, calibrating for plausible values for the

US economy, he concludes that the gains are about one tenth of 1 percentage

point of increased consumption, which is certainly a small number.

Although this framework has been primarily used to assess the benefits

from stabilization policies, it can also be used to evaluate the benefits of world

trade in financial assets. This analysis started with Cole and Obstfeld (1991).

They build a two-country economy, where output shocks leads, in addition to

direct effects on consumption, to changes in terms of trade that automatically

pool output shocks, since the country that is shocked by a positive produc-

tivity shock (in exports) will face a terms of trade deterioration. Calibrating

this model, and considering the offsetting effect coming from terms of trade

fluctuations, for the US and Japan, they conclude that the gains from elim-

inating a ban on portfolio diversification would produce a benefit of at most

0.2 percent of output per year. As in Lucas (1987), the welfare gains from

consumption smoothing, through trade in international financial assets, are

small. The finding that the calibrated gains are relatively small have been

used as an explanation of the “home bias” in international portfolio diversi-

fication, reported, for example, in French and Poterba (1991). They indicate

that US investor hold more than 90% of their equity portfolio in US stocks,

while Japanese investors hold more than 90% of their portfolio in Japanese

stocks. Therefore, there is a tendency of domestic agents to hold a portfolio

heavily bias toward domestic equities, while a non-biased portfolio should be

hold by any individual, regardless of her nationality.

To generate higher welfare gains from international risk-sharing there are a

number of technical assumption that can be relaxed from the original Lucas’

(1987) analysis. A leading example is to break the tight relationship between

the risk-aversion parameter of the utility function and the respective intertem-

poral elasticity of substitution.

11

There are, however, at least two important extensions that need to be con-

sidered when extending the analysis Lucas (1987) and Cole and Obstfeld (1991)

to judge the benefits of financial opening in developing countries. First, the

previous analysis considers two developed economies, where output fluctua-

tions are small and highly correlated, so the scope for consumption smoothing

through risk-sharing is limited. Second, they do not consider that portfo-

lio diversification could produce also an increase in the rate of growth of the

economy, amplifying substantially the welfare gains.

In a couple of papers, van Wincoop (1994a, b) has addressed the first is-

sue, namely, the effects of risk-sharing among countries and regions whose

consumption levels are not highly correlated. In the analysis for consumption

data of 20 OECD countries, van Wincoop (1994a) shows that there are indeed

large unexploited gains from risk-sharing, which amounts to a permanent in-

crease in consumption between 1.7% and 5.6%. The standard deviation of the

rate of growth of consumption of tradable goods for a typical OECD coun-

try is about twice the average rate of growth of tradables consumption for

the aggregate of OECD countries. These results are robust to changes in the

specification of preferences and the parametrization of the model. The main

differences with Cole and Obstfeld (1991), are that they use a very high risk-

less interest rate, risk-sharing is restricted to only two countries, and shocks

are more persistent.

Saint Paul (1992) and Obstfeld (1994) consider another important exten-

sion, which is the growth effects of allowing international trade in assets. There

is a positive effects on consumption smoothing, which spillovers to the pro-

ductive decision of firms. Thus, the static welfare gains from consumption

smoothing are magnified by the growth effects. This literature reinforces the

growth effects of financial development in financially open economies.

Changing the composition of portfolio is the main mechanism in Obstfeld

(1994). He shows that international diversification of risk allows the world

economy to shift portfolio from low-risk low-return investment to higher-risk

high-return investment, which ends up increasing the rate of growth. Interna-

tional financial integration allows each country to hold a globally diversified

12

portfolio for risky capital.

Saint-Paul (1992) develops a model where financial markets affect techno-

logical choice. In this model, agents can choose between two technologies: One

technology is highly flexible and allows productive diversification, but has low

productivity; the other is rigid, more specialized, and more productive. The

economy is exposed to shocks to consumer preferences, which may result in

a lack of demand for some products. Therefore, in the absence of financial

markets risk-averse individuals (consumer-producers) may prefer technologi-

cal flexibility rather than high productivity. Financial markets, in contrast,

allow individuals to hold a diversified portfolio to insure themselves against

negative demand shocks and, at the same time, to choose the more productive

technology.

To study in greater detail the effects of international risk-sharing I develop

a simple model in the spirit of Saint Paul (1992). Consider two countries, 1

and 2, and two goods, 1 and 2. Country 1 produce x of good 1 and y of good

2. Country 2, produces x∗ of good 1 and y∗ of good 2. To simplify technology

I assume that if country 1 does not specialize produces x = q and y = 1 − q,while country 2 produces x∗ = q and y∗ = 1−q, where q > 1/2. Thus, I assume

implicitly that production of each good is unitary, and that country i is more

efficient at good i. In addition, countries can benefit from specialization, due

to, for example, economies of scale. Thus, if country 1 specializes in good 1 it

can produce x = Q > 1, while country 2 could produce y∗ = Q of good 2.

Households are the owners of firms, and the receive as dividend the produc-

tion of firms. Consumers engage in asset trading in period 1, and production

takes place. In period 2, a preference shock is realized and only good 1 (with

probability 0.5) or good two (with probability 0.5) is demanded. Utility for

consuming an amount z of either good is u(z).

In a closed economy, if country 1 specializes in good 1, production will be

Q of good 1 and zero (or perhaps something very small) of good 2. Expected

utility, normalizing the number of consumers to 1, will be Ua = [u(Q)+u(0)]/2.

However, if local production is diversified, expected utility will be Ub = [u(q)+

u(1− q)]/2. In general, given concavity of the utility function and the extent

13

of scale economies, we would expect that the economy will not specialize, and

households in country 1 will have expected utility of Ub. Now, assume that

households can hold shares of foreign companies is s, so the economy is open

to international trade in assets and goods. If the share of portfolio held in

domestic companies, expected utility will be Uc = [u(sx+ (1− s)x∗) + u(sy+

(1− s)y∗)]/2. Two results emerge clearly from this setup: first, countries will

specialize to maximize production, that is x = Q, y∗ = Q, and x∗ = y = 0.

Second, individuals will hold a balanced portfolio with s = 1/2. Thus, utility

will be Uc = [u(Q/2) + u(Q/2)]/2, which can be easily shown to be greater

than Ua, and Ub. Therefore, in general, we have that Uc > Ub > Ua.

Two important conclusions emerge from this analysis. First, individuals are

able to smooth consumption across states of the nature when they are able

to trade in international assets. And second, the inability of individuals to

protect themselves against risk through asset trading may lead them to bad

(second-best) productive decisions. Indeed, in this example, the inability to

trade assets internationally leads them to suboptimal specialization. Thus,

risk-sharing reduces the risk associated with consumption: the variance of

consumption is (q− 1/2)2 across states of nature in the closed economy, while

it is zero in the open economy. On the other hand there is a production effect,

which increases the expected value of consumption from 1/2 in the closed

economy to Q/2 in the open economy.

From an applied point of view it still remains to know whether the gains

from portfolio diversification are relevant, or just small variations from Lucas

(1987). We already saw that the van Wincoop (1994a) has already computed

a welfare gain from pure risk-sharing, without growth effects, equivalent to a

permanent increase in consumption between 2% and 5%. The calibrations in

Obstfeld (1994) show much larger figures. Table 1 shows the potential gains

from risk-sharing. The countries arranged in the horizontal direction of the

table, are all the groups of countries where the rate of growth of consumption

is smaller than the standard deviation of this rate of growth. Besides South

America, they are countries with low growth of consumption. Just by looking

at the first and second moments of the distribution of consumption growth it

14

should be clear that the countries that have most to gain from international

risk-sharing are developing countries. They could increase growth, but also

reduce the variance of consumption. This could be achieved because the cor-

relation of consumption in volatile developing countries with consumption in

industrialized countries plus East Asia is low. Indeed, in many cases the cor-

relation is negative and it is at most 0.44 for the case of South America and

Northern Europe. In effect, the baseline calibrations of Obstfeld (1994)—which

certainly overstate the actual gains but illustrate clearly the differences—show

that, in average, developing countries could gain 370% of initial wealth from

financial integration, while countries arranged in the vertical direction of table

1 could gain in average 77% of wealth, being the lowest East-Asia (22%).

Table 1: Cross-correlation of Consumption

South Central Africa AsiaAmerica America Non-East

{gc - σgc} {3.11 - 4.57} {1.68 - 2.96} {1.31 -3.59} {0.91 - 3.02}North America -0.248 -0.113 -0.415 0.117{2.35 - 1.76}

Northern Europe 0.440 0.289 -0.035 -0.299{2.87 - 1.31}

Southern Europe 0.391 0.115 0.321 -0.166{3.13 - 3.03}

East Asia 0.134 0.365 0.074 -0.299{3.64 - 2.12}

Source: Obstfeld (1994).

gc is average annual rate of consumption growth, 1960-87.

σgc is standard deviation of consumption growth.

The main reason to have those large welfare gains are the growth effects of

full financial integration. Indeed, consumption growth would rise to 4.4% a

year, even higher than the maximum in the actual calculations, that is East

Asia with 3.6%. This sharp increase comes from a drop in the consumption-

to-wealth ratio (increase in savings), but primarily from a shift of world wealth

into riskier high-yield capital. Simulations also show that even if savings fall,

the allocation effect dominates and would result in welfare gains from integra-

tion.

15

Of course, the potential welfare gains are mainly illustrative, since the model

has several shortcuts to reach tractable results. For example, assuming that

there are adjustment costs and capital cannot reallocate instantly, could reduce

to about a third the above mentioned welfare gains. Finally, the model does

not incorporate nontradable goods, and therefore, changes in the real exchange

rate.

Overall, although the literature provides a wide range of estimates for the

benefits of financial integration on welfare due to portfolio diversification, it

is reasonable to conclude that once growth effects are included the welfare

gains for developing countries could be much higher than those associated

with industrialized countries. It is still puzzling, why such diversification has

not already been taking place. As van Wincoop (1994a) has called it, there is

still an “international risksharing puzzle.”

4 Financial Integration and Financial Development

In recent years there has been an explosion of cross-country analysis of growth

determinants. In particular, for our purposes, it has been established that a

deep financial market leads to higher growth, as reviewed in section 2. The

issue I want to examine in this section is whether a high degree of financial in-

tegration leads to an increasing degree of financial development. In particular,

this section attempts to answer the following question:

• Do countries more integrated to world financial markets have deeper fi-

nancial systems?

If this connection exists, then it would follow that financial integration

has an indirect effect on economic growth through the promotion of financial

development.

4.1 Data

The first problem faced to do empirical work is to obtain good indicators of

financial integration. As it was already discussed in the review of the existing

16

empirical evidence there are several indicators for financial development, but

it is more difficult to obtain indicators for financial integration. In this regard

I use data produced by Montiel (1994) and Levine and Zervos (1995).

After having examined a wide variety of indicators I ended up using the

following four indicators:7

1. IAPM (Levine and Zervos, 1995): Indicator based on the international

arbitrage pricing model. To estimate this indicator, the excess return of

a given asset, at a given time, above a risk free asset is regressed against

the excess return on a benchmark portfolio. In the international arbitrage

pricing model the benchmark portfolio is based on the common factors

based on an international portfolio of assets.

If international financial markets are perfectly integrated, there should

be a constant ratio between excess return of an asset and the excess

return of the benchmark portfolio, and hence there should be no intercept

in a regression. Therefore, the higher the intercept, the less integrated

the markets are. In order to have a measure positively correlated with

financial integration, this intercept is multiplied by minus one.

2. ICAPM (Levine and Zervos, 1998): Indicator based on the international

capital asset pricing model. It is very similar to IAPM, but the benchmark

portfolio is constructed on a value-weighted portfolio of common stocks.

IAPM and ICAPM are computed using data for the period 1976–93. For

both indices Levine and Zervos (1995) compute also their value at the

beginning of the estimation period, to have the initial value of IAPM and

ICAPM, but the number of observations declined from 24 to 13.

3. GFR (Montiel, 1994): This corresponds to an indicator of the magnitude

of gross capital flows ratio to GDP for the period 1980–89. A 1 was

assigned for countries with ratio above 20 percent, 2 for countries with

flows between 15 and 20 percent, 3 for a range between 10 and 15 percent,

4 for a range between 5 and 10 percent, and finally a 5 for values below 5

7These indicators are well explained in the papers referred above and in the references therein, and hence,

I discuss them briefly.

17

percent. In order to have an indicator positively correlated with financial

integration I multiply this indicator by minus one.

4. CLAS (Montiel, 1994): It takes a value of 3 for countries highly integrat-

ed internationally, 2 for moderately integrated countries, and 1 for low

integration. It is constructed based in a series of other indicators: GFR,

test results of the Feldstein-Horioka findings, on Euler equation estima-

tions, and tests of uncovered interest parity differentials. I also used the

specific components in the regression analysis, but the results were not

interesting.

To compare financial integration with financial development (or depth) it

is necessary a good set of indicators of financial depth. For this purpose is

important to distinguish among different institutions in capital markets. In

particular, a relevant distinction is between the banking system and stock

markets, since they presumably interact in different forms with international

financial markets. To measure financial depth the following indicators are used

(all of them from Levine and Zervos (1995)):

1. CREDIT: as discussed in the previous section this is total loans made by

the banking system to the private sector. This variable is a good proxy

of the intermediation made by the banking system.

2. MCAP: this is the value of listed shares as a fraction of GDP. Thus, this

indicates the size of the stock market. However, this is an incomplete

picture of the stock market since it ignores the liquidity of the market.

3. TVT: this is the total value of shares traded in a year over GDP. Then,

this is a measure of liquidity of the stock market related to the size of the

economy.

4. VOL: this is a measure of volatility. Besides intermediation provided

by stock markets, an important characteristic of them is their volatility,

which among policymakers, and many economists, is usually thought as

being excessive. For this reason it is important to analyze what is the

effect of financial integration on volatility. It is measured as the twelve-

month rolling standard deviation based on a regression of stock returns.

18

Table 2 presents cross-correlations among indicators of financial integration.

The figures in square brackets are the number of observations. There are about

24 data points per proxy of financial integration, which limits the reliability

of cross-section analysis. However, it is interesting to note that the sample

available with the data of Levine and Zervos (1995) is different to that of

Montiel (1994), since they have in common about half of data points. Thus

when we change variables, we are also looking at a different sample of countries,

which helps to check robustness. The main difference between the two datasets

is that the first one contains some developed countries, while Montiel (1994)

has only developing countries. Therefore, when using IAPM and ICAPM we

will be looking at a sample of both, developing and industrialized countries.

In contrast, when looking at GFR and CLAS we will be examining a sample

of similar size to those based on IAPM and ICAPM, but only containing

developing countries.

An additional difference is the high correlation between IAPM and ICAP-

M, and between CLAS and GFR, but a weak correlation, and in some cases

negative, between the two groups of variables. This fact also helps to check

robustness, since the indicators are not highly correlated.

Table 2: Cross-Correlations andSummary Statistics

IAPM ICAPM CLAS GFRIAPM 1.00

[24]ICAPM 0.92 1.00

[24] [24]CLAS 0.07 0.04 1.00

[12] [12] [22]GFR -0.54 -0.44 0.56 1.00

[14] [14] [22] [24]Average -4.30 -4.08 1.86 -3.63

Stad. dev. 1.47 1.86 0.77 1.28Min. value -6.67 -9.98 1.00 -5.00Max value -2.17 -2.00 3.00 -1.00

Figures in square brackets are No. of observations.

19

4.2 Empirical evidence

The relationship between financial integration (FI) and financial development

(FD) is presented in table 3. The table reports the results of running the

following regression:

FDi = constant+ αFIi + other regressors, (7)

for all four indicators of FD and using each one of the four indicators of

financial integration as dependent variable. The table presents the estimates

of the coefficient α and its t-statistic. In the regressions under the column (1)

there is no other regressor. In order to include the effects that different levels

of development have on the size of the financial system, regressions in columns

(2) include the initial level of GDP per capita as an additional regressor.

In columns (3) two additional regressors where added: average inflation,

and openness (exports plus imports over GDP). Presumably, the rate of in-

flation should have an effect on the development of the financial system. In

general, macroeconomic conditions should affect the development of the finan-

cial system. On the one hand, high inflation may inhibit the development

of the financial system by the uncertainty about financial conditions even at

short horizons, but, on the other hand, one could expect that high inflation

may promote the development of short term and indexed securities to hedge

against inflation. One could expect that long term contracts tend to disappear

in high-inflation experiences, while short term contracts and highly liquid se-

curities tend to emerge. Although the net effect is unclear, high inflation will

change maturity toward short term and liquid instruments.

Trade openness, in addition to financial integration, is the other impor-

tant component of openness. All financial services involved in international

transactions may promote the development of the financial system.

For the presentation of results, columns (3) report regressions only with

significant coefficients for the other regressors. All regressions have between

22 and 24 observations and the R2’s are between 0.5 and 0.7 in those more

general regressions.

Regarding development of the banking system (CREDIT), table 3 shows

20

Table 3: Financial Integration and Financial Development

Financial Indicator of Financial DevelopmentIntegration CREDIT MCAPIndicator (1) (2) (3) (1) (2) (3)

IAPM 0.134∗∗ 0.122∗∗ 0.081∗ 0.059∗∗ 0.052∗∗ 0.040∗

(2.21) (2.64) (1.86) (2.10) (2.65) (1.82)

ICAPM 0.106∗∗ 0.108∗∗ 0.033∗∗ 0.067∗∗ 0.063∗∗ 0.090∗∗

(2.72) (3.96) (3.64) (2.74) (4.25) (5.84)

CLAS 0.239∗∗ 0.187∗∗ 0.093∗ 0.112 0.052 -0.070(3.05) (2.66) (1.80) (0.96) (0.39) (-0.61)

GFR 0.099 0.070 -0.038 0.061 0.034 -0.083(1.51) (1.14) (-1.07) (0.76) (0.42) (-1.42)

Financial Indicator of Financial DevelopmentIntegration VOL TVTIndicator (1) (2) (3) (1) (2) (3)

IAPM -0.026∗∗ -0.026∗∗ -0.008∗ 0.011 0.007 -0.014(-3.55) (-3.45) (-1.61) (0.34) (0.21) (-0.35)

ICAPM -0.030∗∗ -0.030∗∗ -0.013∗∗ 0.025∗∗ 0.026∗∗ 0.029∗∗

(-6.16) (-6.27) (-3.00) (2.13) (3.16) (2.19)

CLAS -0.056 -0.010 -0.025∗∗ 0.047∗ 0.036 0.003(-1.47) (-1.47) (-2.24) (1.75) (1.39) (0.22)

GFR 0.006 -0.012 -0.008∗∗ 0.017 0.010 -0.023∗∗

(0.44) (-1.37) (-2.32) (0.82) (0.52) (-3.33)t statistics in parenthesis.∗ and ∗∗ significant at 10% and 5%, respectively.

(1) No additional regressors.

(2) Includes initial GDP as regressor.

(3) Includes initial GDP, inflation and openness as additional regressors, when significant.

21

that this is the variable most affected by almost all of the indicators of financial

integration. Indeed, for IAPM, ICAPM and CLAS, the coefficient is always

positive and significantly different from zero. As expected, and due to the

positive correlation between financial integration and per capita GDP, as well

as financial opening, the coefficient declines as regressors are added to the

basic regression, but it is still positive. Only for GFR the coefficient is not

different from zero. Therefore, it can be argued that these results support the

hypothesis that increased financial integration leads to increase development

of the domestic banking system.

The size (MCAP) and liquidity (TVT) of the stock market are in general

positively correlated with the degree of integration, when measured by indi-

cators of stock market integration, but not with more general indices, such as

CLAS and GFR.

Another strong correlation found is that integration is associated with less

volatile stock markets. One could suspect that this is the result that less

volatile countries are also more developed, but this result is particularly im-

portant when other regressors are included, and initial per capita GDP did

not appear to be significant. This result is robust to changing variables and

moving from a sample of developed and developing countries (IAPM and I-

CAPM) to one with only developing countries (CLAS and GFR). This result

contrasts with Levine and Zervos (1998), who find that although capital ac-

count liberalization deepens the stock market, it also increases its volatility.

Regarding results for other regressors, there are some interesting findings.

First, regarding inflation it was found that it has a strong positive correlation

with volatility and negative correlation with credit from the banking system

to the private sector. Countries with high rates of inflation tend to have

more volatility in their stock markets. This may be the consequence of large

relative price changes that usually are associated with high inflation,8 and the

resulting change in relative profitability across firms and sectors, which should

8Existing empirical evidence shows that the variability of prices across goods and the variability of prices

of a same good across stores increase with the rate of inflation. See Lach and Tsiddon (1992) and references

therein.

22

be reflected in variability of stock prices.

At the same time, countries with high inflation tend to have a less developed

(measured through CREDIT) banking system. Nevertheless, to a lower extent,

it was found that market capitalization was higher in countries with high

inflation. Perhaps the increased market capitalization with the reduction of

credit intermediated through the banking system is precisely the result of

moving to short term contracts and liquid assets, inducing a raise in the size

of the stock markets. For TVT, the effects of inflation are not significantly

different from zero.

Second, trade openness is positively associated to CREDIT, MCAP and

TVT. This result suggests that may be international integration, financial and

commercial, what promotes a deeper domestic financial market, rather than

purely financial integration.

Finally, countries with higher initial per capita of GDP are countries with

deeper financial systems (CREDIT, MCAP, and TVT), but there is no rela-

tionship to volatility. Therefore, the size of the economy is uncorrelated with

volatility of the stock market.

5 Financial Integration and Economic Growth

In the previous section it was established that indeed there is a positive cor-

relation between financial integration and the development of the domestic

financial market. This section goes one step further examining the effect of

international financial integration on economic growth. In particular, in this

section I attempt to answer the following questions:

• Do countries with more financial integration have higher growth?

• Is there a different channel, to the usual effect of financial development,

from financial integration to economic growth?

23

5.1 Interactions among financial deepening, integration and growth

As it has been discussed before, recent evidence tends to support the view that

countries with more developed financial markets grow faster. The sample and

variables used in this paper confirm that result.

To explore the relationship between financial integration, financial devel-

opment and economic growth I present some cross-section evidence on the

determinants of the rate of per-capita GDP growth during the period 1976–

1993. Following the tradition, I regress the rate of growth of per-capita GDP

on a set of regressors, which include indicators of financial deepening and

indicators of international financial integration.

In table 4, rows “Base 1” and “Base 2” present basic regressions between fi-

nancial deepening indicators (CREDIT, MCAP, VOL and TVT) and economic

growth. In addition to the financial deepening variable, the base regressions

include initial per-capita GDP, initial secondary school enrollment ratio and

revolution and coups as indicators of political instability and degree to which

property rights are protected. The difference between Base 1 and Base 2 is

the sample. Base 1 uses the sample of 24 countries for which there are obser-

vations for ICAPM and IAPM, and as explained above, includes developing

and industrialized countries. Base 2, in contrast, includes only countries for

which there are observations for the variables CLAS and GFR, and therefore,

includes only developing countries. The coefficient of the financial develop-

ment indicators are shown in square brackets, while the others correspond to

the coefficients on the financial integration proxy.

The table confirms previous findings of a positive relationship between fi-

nancial deepness and economic growth. Indeed, CREDIT is positively associ-

ated with growth. Also, and consistent with the results of Levine and Zervos

(1995), countries with a highly capitalized and active stock market grow faster.

However, there seems to be no relationship between stock market volatility and

economic growth, contrary to the negative relationship found by Levine and

Zervos (1995). The reason for this difference is that the latter study considers

a sample of 36 countries, while in this paper I use only 24 observations due

24

to the limitations imposed by the availability of indicators for international

financial integration.

Table 4: Interactions: Financial Integration, Financial Deepeningand Economic Growth

Dependent variable: GDP per capita growthCREDIT MCAP VOL TVT

IAPM -0.00061 [0.034∗∗] 0.002 [0.022] 0.0036 [0.016] 0.003∗ [0.048∗∗](-0.33) [(4.45)] (0.86) [(1.45)] (0.31) [(1.33)] (1.90) [(5.42)]

ICAPM -0.00053 [0.035∗∗] 0.0018 [0.018] 0.0069∗ [0.130] 0.0019∗ [0.045∗∗](-0.42) [(4.07)] (0.95) [(0.93)] (1.89) [(1.28)] (1.90) [(4.59)]

CLAS -0.016 [0.062∗∗] -0.0076 [0.037∗∗] 0.0036 [-0.002] -0.008 [0.212∗∗](-1.40) [(4.62)] (-0.77) [(3.37)] (0.36) [(-0.03)] (-0.89) [(3.91)]

GFR -0.011∗∗ [0.057∗∗] 0.010∗∗ [0.043∗∗] 0.003 [-0.012] 0.009∗∗ [0.200∗∗](-2.78) [(4.66)] (2.77) [(3.19)] (0.28) [(-0.15)] (2.48) [(4.33)]

Base 1 [0.033∗∗] [0.027∗∗] [-0.028] [0.048∗∗][(4.62)] [(2.05)] [(-0.75)] [(3.78)]

Base 2 [0.048∗∗] [0.033∗∗] [-0.009] [0.205∗∗][(3.49)] [(3.01)] [(-0.11)] [(4.03)]

In each cell the first figure is the coefficient of the financial integration indicator. t statistics in parenthesis.

In square bracket coefficient of the financial deepening indicator.

Base 1: equation omitting financial integration indicator, sample based on IAPM and ICAPM.

Base 2: equation omitting financial integration indicator, sample based on CLAS and GFR.∗ and ∗∗ significant at 10% and 5%, respectively.

It is interesting to note that the base regressions confirm the finding of De

Gregorio and Guidotti (1995) that financial development has a stronger effect

on growth in developing countries. As the table shows, the coefficient of the

financial development indicator is greater in the regressions that constraint

the sample to only developing countries. When industrialized countries are

included (base 1), the coefficient is smaller. The novel finding is that this

effect is not only valid for banking development (CREDIT) as discussed in

De Gregorio and Guidotti (1995), but also for the development of the stock

market.

25

In table 4, the coefficient of the financial deepening indicator are still pos-

itive, in most of the cases, when the financial integration indicators are in-

cluded. This is particularly the case of CREDIT and TVT. The collinearity

between MCAP and the indicators of integration of stock markets (IAPM

and ICAPM) makes all of these variables to be not significant when they are

included jointly.

Regarding the effects of financial integration on economic growth table 4

shows that financial integration has no additional effect on economic growth,

beyond the effects that it may have on financial deepening of the domestic

financial market. As reported in table 3, financial integration tends to make

the domestic financial market deeper. However, beyond this effect, there is

no additional effect of financial integration on economic growth. Only GFR

appears to be significant, but changing signs across regressions, and hence,

without clear implication.

5.2 The total effect of financial integration on growth

After establishing that in the sample and with the data of this paper there is no

independent relationship between financial integration and economic growth,

one may want to examine “net” effect of financial integration on economic

growth. To this extent, I present results of regressing per-capita GDP growth

on financial integration indicators, and other regressors, but excluding the

effect of financial depth on economic growth. Thus the financial integration

indicator would capture the effects of financial development on growth.

This analysis is presented in table 5. Three set of regressions were run for

each indicator. The dependent variable is the rate annual rate of growth of per

capita GDP for the period 1976–1993. The first column reports the coefficient

of a regression where the only regressor is the financial integration indicator.

Thus, this regression reports the partial correlation between financial inte-

gration and economic growth. The second column incorporates the financial

integration indicator in a “base” regression, similar to the regressions of table

4, that includes initial per capita GDP, initial secondary school enrollment

26

ratio, and number of revolutions and coups. Finally, the last column includes

in addition to the base regressors, indicators of judicial efficiency, inflation,

government expenditure and black market premium.

Table 5: Financial Integration and Economic Growth

Dependent variable: GDP per capita growthSingle regressor Base regressors Other regressors

IAPM 0.0046∗ 0.0031 0.0026(1.80) [0.08] (1.44) [0.39] (0.89) [0.53]

ICAPM 0.0045∗∗ 0.0029∗∗ 0.0032(3.32) [0.12] (2.57) [0.40] (1.13) [0.53]

CLAS 0.0043 -0.003 -0.0065(0.57) [0.01] (-0.31) [0.14] (-0.76) [0.38]

GFR 0.0021 0.0081∗ -0.0056(0.47) [0.01] (1.66) [0.24] (-0.95) [0.40]

t statistics in parenthesis. R2 in square brackets∗ and ∗∗ significant at 10% and 5%, respectively.

Base regressors: Initial GDP, initial secondary schooling, and number of revo-

lutions and coups.

Other regressors: include in addition index of judicial efficiency, inflation, govern-

ment expenditure and black market premium.

The results of table 5 show that in general there is no correlation between

financial integration and economic growth. Only for ICAPM in the single

and the base regression there is a strong positive relationship between inte-

gration of the stock market and economic growth. However, when additional

regressors are included the positive relationship disappears. For the other

indicators there is no a clear relationship between market integration and e-

conomic growth. Similar conclusions are found by Levine and Zervos (1995),

who report a positive correlation between asset prices indicators of integration

and growth, but, as they explain, these relationships are rather weak, since

they are not robust to the inclusion of other relevant independent variables.

It could be expected that given the broad positive relationship between

financial integration and financial depth, a regression that excludes financial

27

depth, which is positively correlated with growth, and includes financial in-

tegration should show up a positive correlation between financial integration

and economic growth. However, the lack of precision of the estimates may

be the result that the financial integration indicator is a poor proxy of the

financial depth indicator.

An alternative way to analyze the indirect effect of financial integration on

economic growth is to use the coefficients found for the positive relationship

between financial integration and financial depth (table 3) with the coefficients

of table 4 for the base regressions, which evaluates the impact of financial depth

on growth in the sample countries.9 This exercise is presented in table 6. The

main effect on growth is through the deepening of the banking system. An

increase in one standard deviation in IAPM, ICAPM and CLAS increase GDP

growth by 0.5 to 0.7 percentage points. Note that the impact of increasing

in one the value of CLAS (remember that this indicator takes values of 1, 2

and 3) would increase growth by 0.85 percentage points. The effects through

deepening of the stock market are smaller in size, and restricted only to some

indicators, in particular ICAPM.

Table 6: Growth Effects ofFinancial Integration

(percent)

Channel IAPM ICAPM CLAS GFRCREDIT 0.54 0.51 0.66 —

{0.37} {0.27} {0.85} —

MCAP 0.20 0.37 — —{0.14} {0.20} — —

TVT — 0.24 — —— {0.13} — —

The figures are effect changes of one standard deviation

of the indicator of financial integration on growth.

In curly brackets are the effects of a unitary change of the

indicator of financial integration.

9I use only the coefficients that are statistically significant. Since there are three coefficients per indicator

I use the average coefficient.

28

5.3 The effects of foreign direct investment

An important form of international integration is the flow of direct investment

across countries. Foreign investment flows have only secondary effects on over-

all financial development, and via that channel on economic growth. However,

foreign direct investment (FDI) not only represents a form of capital inflows,

but it also may have important effects on technology diffusion, by which de-

veloping countries are able to attract technologies available in more advanced

economies.

The effects of FDI on economic growth have been analyzed by Borensztein,

De Gregorio and Lee (1998).10 They present a model in which the rate of

technological progress is the main determinant of the long-term growth rate.

Technological progress takes place through a process of “capital deepening”

in the form of the introduction of new varieties of capital goods. Multina-

tional corporations possess more advanced “knowledge,” which allows them to

introduce new capital at lower cost. However, the application of these more

advanced technologies requires the presence of a sufficient level of human cap-

ital in the host economy. The stock of human capital in the host country,

therefore, limits the absorptive capability of a developing country.

The effects of FDI on economic growth are tested in a sample of 69 de-

veloping countries over the last two decades. The results suggest that FDI is

in fact an important vehicle for the transfer of technology, as it appears to

contribute to growth in larger measure than domestic investment. Moreover,

a fairly robust finding is that there is a strong complementarily between FDI

and human capital, that is, the contribution of FDI to economic growth is en-

hanced by its interaction with the level of human capital in the host country.

A representative regression is:

γi = −0.72 FDIi + 1.61 FDIi × SCHAi + others

(0.93) (2.55)(8)

R2 = 0.25(0.19), N obs. = 138. where SCHA is male secondary school attain-

10See also De Gregorio (1992) and Blomstrom, Lipsey and Zejan (1992).

29

ment of the population.11

This regression shows that FDI affects growth directly, although in this

specification is insignificant, and also through its interaction with schooling.

The regression indicates that there is a minimum threshold from which FDI

is growth enhancing. In the regression shown here, all countries with sec-

ondary school attainment is above 0.4512 will benefit positively from FDI. In

the sample, 48 out of the 69 countries satisfy this threshold.

6 Concluding Remarks

After reviewing the theoretical literature of financial development, financial

integration and economic growth, this paper presents new evidence on the

effects of financial integration. Although the results are many times weak,

the evidence suggests that there is indeed a positive relationship between the

degree of financial integration and the depth of the domestic financial system.

There is, however, no evidence of direct effect of financial integration on eco-

nomic growth, after controlling for the depth of the domestic capital market.

Therefore, it can be concluded that the beneficial effects of financial integra-

tion on economic growth come mainly through fostering the development of

the domestic financial system. In addition, on top of the growth effects, and

consequently the welfare effects, portfolio diversification may allow a greater

degree of consumption smoothing. There is still a puzzle of why international

portfolio diversification is too small compared to the theoretical prediction-

s. The paper also highlights the benefits of foreign direct investment and its

interactions with human capital.

It is important to note that the findings and focus of this paper refer to

long-run growth effects. I have ignored completely the transitional effects and

how to achieve effective financial integration. Indeed, there is an important

issue of what should come first, financial development or financial integration.

As many country experiences show, opening the capital account in a weakly

11According to Barro and Lee (1994) this is the measure of school attainment most correlated with growth.

12Meaning a male population above 25 years with an average of 0.45 years of secondary schooling.

30

regulated financial system may exacerbate the problem of lack of regulation

with the consequent effect on the ability of the financial system to perform

adequately its role of credit allocation. In addition, as the recent experience

with the surge of capital inflows illustrates, it may be necessary to graduate and

smooth the integration of financial markets in order to preserve macroeconomic

stability. All of these issues are outside the scope of this paper, but they are

essential in designing a beneficial integration with the rest of the world.

31

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